According to the studies carried out in recent years, determination of the regional proposal is one of the crucial steps in detection and recognition of the objects included in an image. In fact, determination of this region has been like a bottleneck, gaining a significant computational energy. As a result, selection of suitable and fast approaches, under these circumstance, may enhance the performance of the recognition system. In this paper, a review was provided on the recent studies carried out in this field of research and few of the famous and friendly approaches conventionally used in the strong recognition systems were introduced and applied on the dataset of PASCAL VOC, ImageNet and COCO. The results obtained indicated that the multiclass combinatorial grouping (MCG) method with the region-convoulational neural network (R-CNN) can provide the best results with the efficiency of 57%, 54% and 41% on the dataset of PASCAL VOC 2007, ImageNet 2013 and COCO 2014 respectively.